Trying to document processes, create training manuals, and generally codify working practices is a common and laudable practice among every organisation.

What can be tricky, though, is deciding where to draw the line. How strict and prescriptive should processes be? Too lax, and mistakes and inconsistencies will creep in; too strict, and the processes will be brittle, failing to adapt to new situations and demands.

One key consideration, I think, is to leave room for mêtis: the tacit knowledge that experienced people on the ground have. The more people can develop and use mêtis, the more effective an organisation is likely to be. This week’s article is about what exactly mêtis is, and why it’s important.

This week’s article

The merits of mêtis

Why is work-to-rule effective as a way of workers negotiating with employers? Isn’t doing your job according to its description what you’re supposed to do? The answer lies in all the tacit, subtle, commonsensical things that employees do every day – in other words, in mêtis.

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This week’s five interesting links

The Economist’s best books of 2021

The end-of-year lists are trickling out; Christmas must be around the corner. The Economist’s best books of 2021 is well worth a dig.

Three highlights from among many:

“Empire of Pain”, by Patrick Radden Keefe

“This is the tragic, enraging story of the Sackler family, the previously low-profile owners of Purdue Pharma – which in 1996 introduced the drug OxyContin. The author shows how an epidemic of prescription-opioid abuse morphed into a worse one of illicit heroin and, later, fentanyl.”

“We Are Bellingcat”, by Eliot Higgins

“How did a bunch of self-taught internet sleuths help solve some of the biggest crimes of recent years, such as the downing of flight MH17 over Ukraine and the Salisbury poisonings? Bellingcat’s founder chronicles some of the outfit’s investigations, and its efforts to galvanise citizen journalists, expose war crimes and pick apart disinformation. An antidote to cyber-miserabilism.”

“Fallen Idols”, by Alex von Tunzelmann

“Ranging from George III to Saddam Hussein, India to the Dominican Republic, this account of the fates of controversial statues – variously dumped, destroyed, moved and re-erected – offers insights into the times and places they were put up and taken down. Statues simplify history, the author says; what is really educational are the arguments they provoke.”


Mel Brooks at 95

Tim Carmody has a great collection of links in celebration of the peerless Mel Brooks’s 95th birthday. Few can beat him for staying power:

“Let’s try to put it in context. Brooks was born in the same year as Queen Elizabeth (II, don’t be cheeky), Marilyn Monroe, and John Coltrane. He’s old enough to have served in World War 2 (which he did), and that he was already in his 40s when he became a filmmaker, with The Producers. People sometimes point out that Barbara Walters, Martin Luther King Jr., and Anne Frank were born in the same year, to note how exact contemporaries can belong to such widely different time periods – yet Brooks is three years older than that trio.”


Omicron Pronunciation Stumps Pretty Much Everyone

Count me among the confused, who’ve been struggling with the correct pronunciation of “omicron” even after looking it up.

That’s partly because of the difference between ancient and modern Greek:

“Even before the pandemic, linguists couldn’t agree on what ancient Greek sounded like, other than that it often didn’t sound like modern Greek. Among scholars, there’s no consensus on how Omicron was pronounced in millennia past. Even in those days, people in different regions spoke their own dialects.

“‘There isn’t one way of saying Omicron,’ said Armand D’Angour, professor of classical languages and literature at the University of Oxford. ‘First of all, you know, we’re not there, we haven’t recorded it.’”

It’s not just coronavirus variants; the world is full of Greek-inspired words, most of which we seem to be collectively mangling.

(When it comes to the name of the coronavirus variant, the least-bad option seems to be “OH-mee-kron”, but it’s probably one of those things – like “chorizo” – where you’re always going to get corrected by someone, and can’t really win.) #

London’s Super-Recognizer Police Force

The Metropolitan Police employ a team of “super-recognisers”, people who are preternaturally able to memorise and recognise faces. They’re aided by the uniquity of CCTV cameras in the UK:

“By some estimates, as many as a million CCTV cameras are installed in London, making it the most surveilled metropolis on the planet. Boris Johnson, who before becoming Britain’s Foreign Secretary served as the city’s mayor, once said, ‘When you walk down the streets of London, you are a movie star. You are being filmed by more cameras than you can possibly imagine.’

“James Rabbett pointed out to me that whereas in Britain people live with the knowledge that ‘ninety per cent of their day’ is captured on camera, ‘a lot of other countries have issues with human rights and that sort of stuff.’”

At one point, the head of the team talks about the capabilities of computer facial recognition systems:

“‘It’s bullshit,’ Mick Neville said when I asked him about automated facial recognition. ‘Fantasyland.’ At the airport, when a scanner compares your face with your passport photo, Neville explained, ‘The lighting’s perfect, the angle’s perfect.’ By contrast, the average human can recognize a family member from behind. ‘No computer will ever be able to do that.’”


The Thinkism Fallacy

Kevin Kelly takes on the fallacy that the application of more intelligence is necessary and sufficient to solve all problems:

“Thinkism is the fallacy that problems can be solved by greater intelligence alone. Thinkism is a fallacy that is often promoted by smart guys who like to think. In their own heads, they think their own success is due to their intelligence, and that therefore more intelligence brings greater success in all things. But in reality IQ is overrated especially as a means to solve problems. This view ignores the many other factors that solve problems. Such as data, experience, and creativity.”